1. Field of the Invention
The invention relates to communication systems, and more particularly to a frequency offset estimation scheme for intersymbol interference channels.
2. Description of the Related Art
Communication channels, and in particular, wireless communication channels, are subject to channel impairments such as multipath propagation in addition to additive noise. In the case of carrier modulation systems, carrier frequency offset that typically occurs due to transmitter and receiver oscillator mismatch in such systems is further compounded by Doppler shifts in mobile RF communications. Rapid frequency acquisition and phase tracking are crucial for accurate decoding of the received information. In general, a large frequency offset gives rise to rapid phase rotation which may be far beyond the tracking capability of a receiver, and of course, seriously degrades the performance of the system. Therefore, estimation and compensation of frequency offset are performance-critical tasks before demodulation at the receiver.
Several known estimation algorithms of frequency offset have been developed on the basis of an ideal channel condition of additive white Gaussian noise (AWGN). In some applications, e.g. a multipath environment, distortion of received signals may introduce considerable intersymbol interference (ISI). The problem of ISI is particularly troublesome in wireless communications. This phenomenon leads to extra noise and degrades the performance of frequency offset estimation.
The presence of ISI thus has to be addressed when designing a scheme to estimate the frequency offset. Scott et al. present a frequency offset estimation algorithm based on applying a nonlinear operation on the received signal, see “Simultaneous Clock Phase and Frequency Offset Estimation,” IEEE Trans. on Commun., Vol. 43, pp. 2263–2270, July 1995. This scheme requires the Fourier transform computations and some approximation based on assumption of the channel impulse response. Conversely, Fechtel et al. disclose algorithms for entirely feedforward joint frame synchronization, frequency offset estimation and channel acquisition, see “Fast Frame Synchronization, Frequency Offset Estimation and Channel Acquisition for Spontaneous Transmission over Unknown Frequency-Selective Radio Channels,” Proc. IEEE PIMRC, pp. 229–233, September 1993. Based on the maximum-likelihood (ML) criterion, Fechtel's method scans data segments of received samples to fulfill the frequency offset estimation. In this scheme, knowledge of the received symbol and symbol timing is required. Bahai et al. reveal that the frequency offset can be estimated by the phase rotation of the channel coefficients, see “A Frequency Offset Estimation Technique for Wireless channels,” in 1997 IEEE Workshop on Signal Processing Advances in Wireless Communications, Paris, April 1997, pp. 397–400. Bahai's algorithm still depends on the transmission of a known symbol pattern. Additionally, Viswanathan et al. propose a method called maximum state-based accumulation (MSA) estimation, refer to “A Frequency Offset Estimation Technique for Frequency-Selective Fading Channels,” IEEE Commun. Letters, Vol. 5, pp. 166–168, April 2001. This technique relies on knowledge of the modulated data in the received signal.
In view of the above, the prior known estimation techniques for ISI channels, however, either have the disadvantage of high computational complexity, or are difficult to implement in integrated circuits.